Autotude

Altitude is a 2d multiplayer game, released in 2009 by Nimbly Games.

This repository is my ongoing attempt to make Altitude a nice environment for reinforcement learning in my (super limited) free time.

So far, we have:

• A protobuf schema that can stream game state at around 12 kbps (raw) or 3 kbps (gzipped).
• An "indexer" that can dump features of replays into a database.
• An in-browser replay viewer.
• A "bot server" that can simulate offline bots faster than realtime.
• A Python interface for controlling bots running on the bot server.

Quickstart

Use direnv to load environment variables from .envrc. Run just nix to build etc/nix.env if you'd like to manage Haxe, Java and protoc through nix. Install the conda environment specified at environment.yml for other dependencies.

If you have the bot-server branch of the Altitude source tree, point to it with ALTI_SRC and run just setup. Then run server tbd_standalone to play Altitude's existing bots against each other on tbd_cave, or run python -m alti_rl to run some bots controllable through Python.

Project Structure

proto/

proto/ contains the message format used to serialize game state, game inputs, and geometry of game objects.

I've patched Altitude (not fully open source) to serialize game state to a stream of Update messages. An Update is roughly a screenshot of all game-relevant state at a given moment in time besides map geometry. This ncludes information not normally available to a player like positions of off-screen planes, powerups held by enemies, and exact health/energy values of all planes.

Once gzipped, streaming a game as a series of Update messages (see proto/update.proto) is roughly as efficient as the netcode used by the game but much less arcane. Most importantly, Updates don't require the reader to simulate any parts of the game, and provide all "game objects" as .

A replay (extension .pb) is just a gzipped sequence of length-delimited Update messages.

The bandwidth of a game with 8 players (like 4v4 ball) tends to be about 0.2 megabytes per minute after gzipping, or roughly 100x less than the bandwidth of 720p video.

data/polys

Map geometry is sent in the first Update message when a game begins. Besides map geometry, the only additional information needed to interpret an Update are the relative hitboxes of game objects like planes and projectiles. data/polys is a gzipped sequence of length-delimited Poly messages (as defined in proto/poly.proto) giving the hixboxes of different game objects. This data is read from poly_src, an bunch of XML files copied from Altitude.

Planes have different hitboxes depending on their "roll." The degrees of roll for which hitboxes are available are irregularly distributed.

hx_src/

Haxe soure. Mainly the replay viewer, written with the heaps game engine.

rust_src/

Rust source for the indexer (bin/index) used to dump replays into a DuckDB database.

viewer/

A web application for browsing and viewing replay files. The app reads from a DuckDB database created by the indexer and provides a web interface to browse and launch replays in the viewer.

To run the viewer:

1. Make sure you have indexed some replays with bin/index
2. Set the DATA_DIR environment variable to point to your data directory
3. Create and activate the conda environment:

   mamba env create -f environment.yml
   mamba activate alti

4. Run python viewer/app.py
5. Open http://localhost:5000 in your browser